An island energy supply configuration method and system

Abstract

The application discloses an island energy supply configuration method and system, and belongs to the technical field of energy system planning and optimal configuration. The method comprises the following steps: S1, island multi-energy resource exploration and energy endowment evaluation processing are performed to generate island energy resource endowment characteristic data; S2, multi-energy complementary power generation unit preliminary configuration processing is performed according to the island energy resource endowment characteristic data to generate multi-energy complementary power generation unit configuration scheme data; and S3, island load demand prediction and dynamic characteristic analysis processing are performed based on the multi-energy complementary power generation unit configuration scheme data to generate island load demand time sequence characteristic data. When the island energy supply configuration is performed, the method integrates various energies such as photovoltaic energy, wind energy, wave energy and diesel power into a unified optimal configuration framework through multi-energy complementary power generation unit preliminary configuration processing, and realizes comprehensive optimal configuration of multi-energy complementation.

Description

Technical Field

[0001] This invention relates to the field of energy system planning and optimization, and in particular to an energy supply configuration method and system for an island. Background Technology

[0002] Citation: CN108009700A A method and system for configuring energy supply on an isolated island;

[0003] Island energy supply refers to the construction of an independent or semi-independent energy supply system by integrating various energy generation, storage, and load management methods to meet the diversified energy needs of island users, such as electricity, heat, and freshwater. Because islands are far from the mainland power grid, it is difficult for them to obtain stable power support through traditional transmission networks. Therefore, they typically rely on diesel generators, photovoltaic power generation, wind power generation, wave power generation, and energy storage systems to build a self-sufficient energy supply system.

[0004] Currently, the main technical challenges in configuring energy supply on islands are as follows: First, islands typically possess multiple renewable energy resources, including solar, wind, wave, and tidal energy, with significant differences in output characteristics among these energy sources. Solar output exhibits peak characteristics during the day, wind output fluctuates wildly due to the randomness of wind speed, and wave and tidal energy show obvious seasonal patterns. Existing configuration methods often employ independent planning for single energy sources, failing to achieve comprehensive and optimized configuration through multi-energy complementarity. Second, island load demand exhibits significant seasonal and intraday fluctuations, with peak-to-valley load differences being particularly pronounced on tourist islands. Existing methods lack refined modeling and adaptive matching capabilities for the dynamic characteristics of load demand. Third, energy storage systems are a crucial regulatory element in island energy supply, but existing configuration methods lack systematic consideration of energy storage system charging and discharging strategies, lifetime degradation characteristics, and multi-timescale scheduling, leading to either excessively large or insufficient energy storage capacity, impacting system economy and reliability. Fourth, the island's freshwater supply and energy supply are highly coupled—seawater desalination requires a large amount of electricity, while the waste heat from the power generation process can be used for seawater desalination. Existing methods often plan energy supply and freshwater supply separately, making it impossible to achieve synergistic optimization of combined power and water production.

[0005] Therefore, a method and system for configuring energy supply on islands is proposed to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to solve the problems in the prior art by proposing an energy supply configuration method and system for islands.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] An energy supply configuration method for an island, the method comprising the following steps:

[0009] S1. Conduct multi-energy resource exploration and energy endowment assessment of the islands to generate island energy resource endowment characteristic data;

[0010] S2. Based on the island's energy resource endowment characteristic data, perform preliminary configuration processing of multi-energy complementary power generation units to generate multi-energy complementary power generation unit configuration scheme data.

[0011] S3. Based on the configuration scheme data of the multi-energy complementary power generation unit, perform island load demand prediction and dynamic characteristic analysis to generate island load demand time series characteristic data.

[0012] S4. Based on the time-series characteristic data of the island's load demand, perform energy storage system capacity optimization configuration and charging / discharging strategy planning to generate energy storage system configuration scheme data and charging / discharging scheduling strategy data.

[0013] S5. Based on the energy storage system configuration scheme data and the charging and discharging scheduling strategy data, perform co-generation power and water production collaborative configuration processing to generate co-generation power and water production system configuration scheme data.

[0014] S6. Based on the configuration scheme data of the multi-energy complementary power generation unit, the configuration scheme data of the energy storage system, and the configuration scheme data of the combined power and water system, perform multi-time-scale joint simulation verification and scheme iterative optimization to generate the optimal configuration scheme data for island energy supply.

[0015] S7. Based on the optimal configuration scheme data for island energy supply, deploy and connect the energy supply system to the grid, and generate system operation status monitoring data;

[0016] S8. Based on the system operation status monitoring data, perform real-time scheduling optimization and adaptive adjustment processing to generate dynamic scheduling optimization instruction data and updated system operation parameter data.

[0017] Preferably, the generation of island energy resource endowment characteristic data in S1 includes the following steps:

[0018] S11. By deploying meteorological monitoring stations and marine monitoring buoys at various points on the island, collect data on annual solar radiation intensity, wind speed sequence, wave height and period, tidal current speed and direction, and generate raw multi-energy resource monitoring data.

[0019] S12. The original multi-energy resource monitoring data is reported to the data center, and the resource assessment engine performs resource potential assessment and uncertainty quantification on various energy resources according to the preset energy resource assessment model, generating data on the annual average utilization hours, guaranteed output rate and fluctuation coefficient of various energy resources.

[0020] S13. Based on the annual average utilization hours, guaranteed output rate and fluctuation coefficient data of the various types of energy resources, combined with the island's geospatial information, available land area and sea area usage conditions, construct a multi-dimensional energy endowment vector with resource category as the dimension, and aggregate to generate the island's energy resource endowment characteristic data.

[0021] Preferably, the generation of multi-energy complementary power generation unit configuration scheme data in step S2 includes the following steps:

[0022] S21. Obtain the energy resource endowment characteristics data of the island;

[0023] S22. Based on the multi-energy complementary optimization configuration model, with the goal of optimizing the system's full life-cycle economy and constrained by power supply reliability, the installed capacity of photovoltaic power generation units, wind power generation units, wave power generation units, and diesel power generation units is jointly optimized. The capacity configuration of each power generation unit is achieved through the following optimization objective function:

[0024]

[0025]

[0026] in, This represents the total cost over the entire system lifecycle. This represents the total number of power generation unit types. For the first The unit capacity investment cost of the power generation unit, For the first Configuration capacity of the power generation unit, For the first The unit power generation operation and maintenance cost of this type of power generation unit. For the first Annual power generation of the type of power generation unit For the unit cost of diesel fuel, For the first Diesel consumption during a given period For the first Class of power generation units in the first Efforts during a specific time period and The energy storage system in the first Discharge power and charging power during the time period For the first Load demand during different time periods This is the power supply reliability margin factor. For time period index, This represents the total number of time periods;

[0027] S23. Based on the optimized configuration results, generate recommended installed capacity and corresponding output curve data for various types of power generation units, which will be used as the configuration scheme data for the multi-energy complementary power generation units.

[0028] Preferably, the generation of island load demand time-series characteristic data in step S3 includes the following steps:

[0029] S31. Obtain historical electricity load data, seasonal tourist flow data, residential energy consumption data, and seawater desalination water demand data for the island;

[0030] S32. Based on the time series decomposition method, load demand is decomposed into trend components, seasonal components, periodic components, and random residual components, and the hourly load demand forecast data for the whole year is generated through the following load forecasting model:

[0031]

[0032] in, For the first Forecasted load demand for the specified period As a trend component, The harmonic order of the seasonal component. and The first The amplitude and phase of the first harmonic. For the corresponding seasonal cycle, Let the order be the autoregressive order. These are the autoregressive coefficients. For the first Actual load value for the time period For random residuals;

[0033] S33. Perform peak-valley characteristic analysis, volatility analysis, and extreme scenario extraction on the hourly load demand forecast data for the whole year to generate the island load demand time series characteristic data containing typical daily load curves, seasonal load characteristics, and peak load scenarios.

[0034] Preferably, the generation of energy storage system configuration scheme data and charge / discharge scheduling strategy data in step S4 includes the following steps:

[0035] S41. Obtain the island load demand time-series characteristic data and the multi-energy complementary power generation unit configuration scheme data;

[0036] S42. Based on the multi-objective optimization configuration model of the energy storage system, with the objectives of maximizing system power supply reliability and minimizing system operating costs, the rated capacity, rated power, and state-of-charge operating range of the energy storage system are optimized. The energy storage capacity configuration is achieved through the following multi-objective optimization function:

[0037]

[0038]

[0039]

[0040] in, For the total lifecycle cost of energy storage systems, Cost per unit power of energy storage This is the rated power of the energy storage. Cost per unit capacity of energy storage For the rated capacity of energy storage, The lifetime degradation cost per unit throughput of energy storage The system power supply failure rate, For the first The probability of load loss during a given period;

[0041] S43. Based on the state of charge constraints and charge / discharge efficiency characteristics of the energy storage system, formulate a multi-timescale charge / discharge scheduling strategy. The charge / discharge scheduling strategy includes three levels: day-ahead planning scheduling, intraday rolling correction, and real-time power balance. Generate the energy storage system configuration scheme data and charge / discharge scheduling strategy data.

[0042] Preferably, the generation of the combined power and water production system configuration scheme data in step S5 includes the following steps:

[0043] S51. Obtain the configuration scheme data of the multi-energy complementary power generation unit and the configuration scheme data of the energy storage system;

[0044] S52. Based on the energy-freshwater coupling optimization model, the electricity demand of the seawater desalination system is incorporated into the comprehensive load system, and the waste heat from the power generation system is used as a heat source for seawater desalination in a cascade manner. Joint optimization is achieved through the following cogeneration coordination configuration function:

[0045]

[0046]

[0047]

[0048] in, The target value for comprehensive optimization of the combined power and water generation system, The total lifecycle cost of a combined power and water system. The total cost of the baseline solution, The system power supply failure rate, The load failure rate is the baseline scheme. To address the freshwater supply shortage. This represents the total freshwater demand. , , These are the weighting coefficients for cost, power supply reliability, and water supply reliability, respectively. For the first Power consumption of the seawater desalination system during a given period For the first Surplus power of the power generation system during certain periods For the first Reserved power available for use by the time-of-use energy storage system. For the first The amount of heat required by the seawater desalination system during a given period For waste heat recovery efficiency, For the first The time-of-use power generation system can recover waste heat;

[0049] S53. Based on the optimization solution results of the combined power and water production configuration function, generate the installed capacity, daily water production, and coupling operation scheme of the seawater desalination system with the power generation system, as the configuration scheme data of the combined power and water production system.

[0050] Preferably, the process of generating the optimal configuration data for island energy supply in step S6 includes the following steps:

[0051] S61. Integrate the configuration scheme data of the multi-energy complementary power generation unit, the configuration scheme data of the energy storage system, and the configuration scheme data of the combined power and water system into an initial comprehensive configuration scheme.

[0052] S62. Based on a multi-timescale joint simulation platform, the initial integrated configuration scheme is simulated and verified hourly for 8760 hours throughout the year. The simulation dimensions include second-level power electronic transient simulation, minute-level power balance simulation and hour-level energy dispatch simulation. The scheme's power supply reliability, water supply reliability and economic indicators are evaluated under various typical scenarios.

[0053] S63. If the simulation verification results do not meet the preset reliability and economic thresholds, the configuration parameters shall be corrected by iteratively optimizing the following scheme:

[0054]

[0055] in, Indicates the first The set of configuration parameters for round iteration. For learning rate, To comprehensively optimize the objectives Regarding configuration parameters gradient, The momentum coefficient;

[0056] Iterate until the convergence condition is met to generate the optimal energy supply configuration scheme data for the island.

[0057] Preferably, the generation of system operation status monitoring data in step S7 includes the following steps:

[0058] S71. Based on the optimal configuration scheme data for island energy supply, deploy photovoltaic arrays, wind turbine generators, wave energy conversion devices, energy storage systems, seawater desalination systems, and intelligent energy management systems on the island site.

[0059] S72. Through intelligent monitoring terminals deployed in each power generation unit, energy storage unit and load node, real-time data on power generation, energy storage state of charge, load power, environmental parameters and equipment health status are collected.

[0060] S73. The collected multi-source data is aggregated to the central monitoring platform, and data cleaning, alignment and fusion processing are performed to generate the system operation status monitoring data.

[0061] Preferably, the generation of dynamic scheduling optimization instruction data and updated system operating parameter data in step S8 includes the following steps:

[0062] S81. Based on the system operation status monitoring data, perform real-time assessment of renewable energy power generation forecast deviation, load demand forecast deviation and equipment operation status.

[0063] S82. When a prediction deviation is detected to exceed a preset threshold or an abnormal operating condition occurs in the equipment, a real-time scheduling optimization process is triggered, generating dynamic scheduling instructions through the following rolling time-domain optimization scheduling model:

[0064]

[0065]

[0066]

[0067] in, To optimize the time domain length, For the first System operating costs during a given period For the first System power imbalance during different time periods and These are operating cost weights and power balance weights, respectively. For the first The state of charge of the time-limited energy storage system and These are the lower and upper limits of the state of charge, respectively. For the first Class of power generation units in the first Efforts during a specific time period Its rated power;

[0068] S83. The dynamic scheduling command is sent to each power generation unit, energy storage system and the actuator of the adjustable load to complete the dynamic adjustment of the system operation status and generate the updated system operation parameter data.

[0069] Preferably, the system includes an island multi-energy resource exploration and assessment module, a multi-energy complementary power generation configuration module, a load demand analysis and forecasting module, an energy storage system optimization configuration module, a combined power and water generation collaborative configuration module, a joint simulation and scheme optimization module, and a real-time scheduling and adaptive control module.

[0070] The island multi-energy resource exploration and assessment module collects island solar radiation, wind speed, wave and tide data through meteorological and marine monitoring probe units, and performs potential assessment and quantification of various energy resources through resource assessment and standardization units to generate unified energy resource endowment characteristic data.

[0071] The multi-energy complementary power generation configuration module receives the energy resource endowment characteristic data, performs joint optimization configuration of the capacity of photovoltaic, wind power, wave energy and diesel power generation units through the multi-energy complementary optimization unit, and outputs multi-energy complementary power generation unit configuration scheme data through the power generation scheme generation unit.

[0072] The load demand analysis and forecasting module receives historical load data and external influencing factor data of the island, generates load demand time series characteristic data through the time series decomposition and forecasting unit, and outputs typical daily load curves and extreme scenario data through the load characteristic analysis unit.

[0073] The energy storage system optimization configuration module receives the load demand time-series characteristic data and the power generation unit configuration scheme data, determines the rated power and rated capacity of the energy storage system through the energy storage capacity optimization unit, and generates multi-time-scale charging and discharging scheduling strategy data through the charging and discharging strategy planning unit.

[0074] The combined power and water production configuration module receives the power generation configuration scheme and the energy storage configuration scheme, and performs joint optimization of the seawater desalination system capacity and the power generation waste heat utilization scheme through the electric-water coupling optimization unit, and outputs the combined power and water production system configuration scheme data.

[0075] The joint simulation and scheme optimization module receives the configuration scheme data from the above modules, performs hourly simulation evaluation throughout the year through the multi-timescale simulation verification unit, and corrects the parameters of schemes that do not meet the constraints through the scheme iteration optimization unit, and outputs the optimal configuration scheme data for island energy supply.

[0076] The real-time scheduling and adaptive control module receives system operation status monitoring data, detects the prediction deviation between power generation and load in real time through the prediction deviation evaluation unit, generates dynamic scheduling optimization instructions through the rolling time domain optimization scheduling unit, and completes the dynamic adjustment of system operation status through the execution control unit.

[0077] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0078] 1. In this invention, when configuring island energy supply, a preliminary configuration process of multi-energy complementary power generation units is used to incorporate various energy sources such as photovoltaic, wind power, wave energy, and diesel power generation into a unified optimization configuration framework. This achieves comprehensive optimization configuration of multi-energy complementarity, and can adaptively determine the optimal capacity ratio of various power generation units according to the island's differentiated resource endowment conditions. This effectively overcomes the problems of resource waste and low system efficiency caused by independent planning of a single energy source, and significantly improves the utilization rate of renewable energy and the economic efficiency of the energy supply system on the island.

[0079] 2. In this invention, when configuring island energy supply, load demand time-series characteristic data is generated through island load demand forecasting and dynamic characteristic analysis. This data comprehensively covers the trend component, seasonal component, periodic component, and random fluctuation characteristics of the load. Based on this data, the energy storage system is optimized through multi-objective configuration and multi-timescale charging and discharging strategy planning, achieving precise matching between energy storage capacity configuration and load dynamic characteristics. At the same time, through real-time scheduling optimization and adaptive adjustment, the system operation strategy can be dynamically adjusted when renewable energy output fluctuates and load demand changes, thereby effectively solving the problems of unreasonable energy storage configuration and lack of scheduling flexibility, and improving the power supply reliability and operating economy of the system.

[0080] 3. In this invention, when configuring the integrated energy supply for an island, the electricity demand of the seawater desalination system is incorporated into the integrated load system through the coordinated configuration of combined power and water generation. The waste heat from the power generation system is used as a heat source for seawater desalination in a cascade manner, thus achieving joint optimization of energy supply and freshwater supply. At the same time, through multi-timescale joint simulation verification and iterative optimization of the scheme, the combined power and water generation scheme is simulated and evaluated and the parameters are iteratively corrected throughout the year, ensuring the feasibility and robustness of the scheme in actual operation. This effectively solves the problem of separate planning of energy supply and freshwater supply, and realizes the coordinated and efficient utilization of island power and water resources. Attached Figure Description

[0081] Figure 1 This is a flowchart illustrating an energy supply configuration method for an island according to the present invention;

[0082] Figure 2 This is a schematic diagram of an energy supply configuration system for an island according to the present invention. Detailed Implementation

[0083] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0084] Please see Figure 1 - Figure 2 The method and system for configuring energy supply on an island include the following steps:

[0085] S1. Conduct multi-energy resource exploration and energy endowment assessment of the islands to generate island energy resource endowment characteristic data;

[0086] S2. Based on the island's energy resource endowment characteristics data, perform preliminary configuration processing of multi-energy complementary power generation units to generate multi-energy complementary power generation unit configuration scheme data;

[0087] S3. Based on the configuration scheme data of multi-energy complementary power generation units, perform island load demand forecasting and dynamic characteristic analysis to generate island load demand time series characteristic data.

[0088] S4. Based on the time-series characteristic data of island load demand, optimize the configuration of energy storage system capacity and plan the charging and discharging strategy to generate energy storage system configuration scheme data and charging and discharging scheduling strategy data.

[0089] S5. Based on the energy storage system configuration scheme data and the charging and discharging scheduling strategy data, perform co-generation of electricity and water to generate co-generation system configuration scheme data.

[0090] S6. Based on the configuration scheme data of multi-energy complementary power generation units, energy storage system, and combined power-water system, perform multi-timescale joint simulation verification and scheme iterative optimization to generate the optimal configuration scheme data for island energy supply.

[0091] S7. Based on the optimal configuration scheme data for island energy supply, deploy and connect the energy supply system to the grid, and generate system operation status monitoring data;

[0092] S8. Based on system operation status monitoring data, perform real-time scheduling optimization and adaptive adjustment processing to generate dynamic scheduling optimization instruction data and updated system operation parameter data.

[0093] The steps involved in generating island energy resource endowment characteristic data in S1 are as follows:

[0094] S11. By deploying meteorological monitoring stations and marine monitoring buoys at various points on the island, collect data on annual solar radiation intensity, wind speed sequence, wave height and period, tidal current speed and direction, and generate raw multi-energy resource monitoring data.

[0095] S12. The raw multi-energy resource monitoring data is reported to the data center, and the resource assessment engine performs resource potential assessment and uncertainty quantification on various energy resources according to the preset energy resource assessment model, generating data on the annual average utilization hours, guaranteed output rate and fluctuation coefficient of various energy resources.

[0096] S13. Based on the annual average available hours, guaranteed output rate and fluctuation coefficient data of various energy resources, combined with island geospatial information, available land area and sea area use conditions, construct a multi-dimensional energy endowment vector with resource category as the dimension, and aggregate to generate island energy resource endowment characteristic data.

[0097] The steps involved in generating multi-energy complementary power generation unit configuration scheme data in S2 are as follows:

[0098] S21. Obtain data on the characteristics of island energy resource endowment;

[0099] S22. Based on the multi-energy complementary optimization configuration model, with the goal of optimal economic efficiency throughout the system's life cycle and the constraint of power supply reliability, the installed capacity of photovoltaic power generation unit, wind power generation unit, wave power generation unit and diesel power generation unit is jointly optimized and configured.

[0100] S23. Based on the optimization configuration results, generate recommended installed capacity and corresponding output curve data for various types of power generation units, which will serve as configuration scheme data for multi-energy complementary power generation units.

[0101] Generating island load demand time-series characteristic data in S3 includes the following steps:

[0102] S31. Obtain historical electricity load data, seasonal tourist flow data, residential energy consumption data, and seawater desalination water demand data for the island;

[0103] S32. Based on the time series decomposition method, the load demand is decomposed into trend components, seasonal components, periodic components and random residual components to generate hourly load demand forecast data for the whole year.

[0104] S33. Perform peak-valley characteristic analysis, volatility analysis, and extreme scenario extraction on the hourly load demand forecast data throughout the year to generate island load demand time series characteristic data that includes typical daily load curves, seasonal load characteristics, and peak load scenarios.

[0105] The steps involved in generating energy storage system configuration data and charge / discharge scheduling strategy data in S4 are as follows:

[0106] S41. Obtain island load demand time-series characteristic data and multi-energy complementary power generation unit configuration scheme data;

[0107] S42. Based on the multi-objective optimization configuration model of the energy storage system, with the objectives of maximizing the system power supply reliability and minimizing the system operating cost, the rated capacity, rated power and state-of-charge operating range of the energy storage system are optimized.

[0108] S43. Based on the state of charge constraints and charge / discharge efficiency characteristics of the energy storage system, formulate a multi-timescale charge / discharge scheduling strategy. The charge / discharge scheduling strategy includes three levels: day-ahead planning scheduling, intraday rolling correction, and real-time power balance. Generate energy storage system configuration scheme data and charge / discharge scheduling strategy data.

[0109] The steps involved in generating the configuration scheme data for the combined power and water generation system in S5 are as follows:

[0110] S51. Obtain configuration scheme data for multi-energy complementary power generation units and configuration scheme data for energy storage systems;

[0111] S52. Based on the energy-freshwater coupling optimization model, the power demand of the seawater desalination system is incorporated into the comprehensive load system, and the waste heat of the power generation system is used as a heat source for seawater desalination in a cascade manner. Joint optimization is achieved through the power-water cogeneration collaborative configuration function.

[0112] S53. Based on the optimization solution of the co-generation configuration function, generate the installed capacity, daily water production and coupling operation scheme of the seawater desalination system with the power generation system, as the configuration scheme data of the co-generation system.

[0113] The steps involved in generating the optimal energy supply configuration data for the island in S6 are as follows:

[0114] S61. Integrate the configuration scheme data of multi-energy complementary power generation units, energy storage system, and combined power-water system into an initial comprehensive configuration scheme.

[0115] S62. Based on a multi-timescale joint simulation platform, the initial integrated configuration scheme is simulated and verified hourly for 8760 hours throughout the year. The simulation dimensions include second-level power electronic transient simulation, minute-level power balance simulation and hour-level energy dispatch simulation. The scheme is evaluated in terms of power supply reliability, water supply reliability and economic indicators under various typical scenarios.

[0116] S63. If the simulation verification results do not meet the preset reliability threshold and economic threshold, the configuration parameters are corrected through the scheme iterative optimization equation, and the iteration continues until the convergence condition is met, generating the optimal configuration scheme data for island energy supply.

[0117] Generating system operation status monitoring data in S7 includes the following steps:

[0118] S71. Based on the optimal configuration scheme data for island energy supply, deploy photovoltaic arrays, wind turbine generators, wave energy conversion devices, energy storage systems, seawater desalination systems, and intelligent energy management systems on the island site.

[0119] S72. Through intelligent monitoring terminals deployed in each power generation unit, energy storage unit and load node, real-time data on power generation, energy storage state of charge, load power, environmental parameters and equipment health status are collected.

[0120] S73. Collect multi-source data and aggregate it to the central monitoring platform for data cleaning, alignment and fusion processing to generate system operation status monitoring data.

[0121] The steps involved in generating dynamic scheduling optimization instruction data and updated system operating parameter data in S8 are as follows:

[0122] S81. Based on system operation status monitoring data, conduct real-time assessment of renewable energy power generation forecast deviation, load demand forecast deviation, and equipment operation status;

[0123] S82. When the prediction deviation is detected to exceed the preset threshold or the equipment is in an abnormal operating condition, the real-time scheduling optimization process is triggered, and dynamic scheduling instructions are generated by the rolling time domain optimization scheduling model.

[0124] S83. The dynamic dispatch command is sent to the actuators of each power generation unit, energy storage system and adjustable load to complete the dynamic adjustment of the system operation status and generate updated system operation parameter data.

[0125] The system includes a multi-energy resource exploration and assessment module for islands, a multi-energy complementary power generation configuration module, a load demand analysis and forecasting module, an energy storage system optimization configuration module, a power-water cogeneration collaborative configuration module, a joint simulation and scheme optimization module, and a real-time scheduling and adaptive control module.

[0126] The island multi-energy resource exploration and assessment module collects solar radiation, wind speed, wave and tide data of the island through meteorological and marine monitoring probe units. Through resource assessment and standardization units, it conducts potential assessment and quantification of various energy resources to generate unified energy resource endowment characteristic data.

[0127] The multi-energy complementary power generation configuration module receives energy resource endowment characteristic data, performs joint optimization configuration of the capacity of photovoltaic, wind power, wave energy and diesel power generation units through the multi-energy complementary optimization unit, and outputs multi-energy complementary power generation unit configuration scheme data through the power generation scheme generation unit.

[0128] The load demand analysis and forecasting module receives historical load data and external influencing factor data of the island, generates load demand time series characteristic data through the time series decomposition and forecasting unit, and outputs typical daily load curves and extreme scenario data through the load characteristic analysis unit.

[0129] The energy storage system optimization configuration module receives load demand time-series characteristic data and power generation unit configuration scheme data, determines the rated power and rated capacity of the energy storage system through the energy storage capacity optimization unit, and generates multi-time-scale charging and discharging scheduling strategy data through the charging and discharging strategy planning unit.

[0130] The combined power and water generation configuration module receives the power generation configuration scheme and the energy storage configuration scheme. Through the combined power and water coupling optimization unit, it performs joint optimization on the seawater desalination system capacity and the power generation waste heat utilization scheme, and outputs the combined power and water generation system configuration scheme data.

[0131] The joint simulation and scheme optimization module receives the configuration scheme data from the above modules, performs hourly simulation evaluation throughout the year through the multi-timescale simulation verification unit, and corrects the parameters of schemes that do not meet the constraints through the scheme iteration optimization unit, and outputs the optimal configuration scheme data for island energy supply.

[0132] The real-time scheduling and adaptive control module receives system operation status monitoring data, detects the prediction deviation between power generation and load in real time through the prediction deviation assessment unit, generates dynamic scheduling optimization instructions through the rolling time domain optimization scheduling unit, and completes the dynamic adjustment of system operation status through the execution control unit.

[0133] An energy supply configuration method and system operation steps for an island are as follows:

[0134] Step 1: Island Multi-Energy Resource Exploration and Energy Endowment Assessment:

[0135] This step is fundamental to the entire methodology, aiming to comprehensively survey and quantitatively assess the various renewable energy resources possessed by the island. The system continuously collects multi-energy resource data, including solar radiation, wind speed, waves, and tides, throughout the year through meteorological monitoring stations and marine monitoring buoys deployed at various points on the island. This data is then reported to the data center. Based on a pre-defined energy resource assessment model, the data center performs resource potential assessments and uncertainty quantification on various energy resources, eliminating differences between different data sources and units. Combining this with the island's geospatial information and available land area, it constructs unified and standardized energy resource endowment characteristic data, laying the foundation for subsequent multi-energy complementary optimal allocation.

[0136] Step 2: Preliminary configuration of multi-energy complementary power generation units:

[0137] After obtaining a unified energy resource endowment characteristic, the system jointly optimizes the installed capacity of various power generation units. Specifically, based on a multi-energy complementary optimization configuration model, with the goal of optimizing the system's full life-cycle economy and constrained by power supply reliability, the system collaboratively optimizes the installed capacity of photovoltaic, wind, wave, and diesel power generation units. This process fully considers the complementary characteristics of the output time sequence of various energy sources—photovoltaic output is strong during the day and zero at night, wind power can operate around the clock but fluctuates significantly, and wave energy exhibits seasonal patterns—achieving multi-energy complementarity through reasonable capacity allocation, thereby constructing a power generation system configuration scheme that combines excellent economy and reliability.

[0138] Step 3: Island Load Demand Forecasting and Dynamic Characteristic Analysis:

[0139] To accurately match energy supply and load demand, the system performs refined forecasting and characteristic analysis of the island's energy load. The system acquires multi-dimensional data including historical electricity load, seasonal tourist flow, residential energy consumption, and seawater desalination water demand. Based on time series decomposition methods, it breaks down load demand into trend, seasonal, periodic, and random components, generating hourly load demand forecasts for the entire year. Subsequently, the system analyzes the peak-valley characteristics, volatility, and extreme scenarios of the forecast data, extracting typical daily load curves and peak load scenarios to form time-series characteristic data that comprehensively depicts the dynamic characteristics of the island's load.

[0140] Step 4: Energy storage system capacity optimization and charging / discharging strategy planning:

[0141] Energy storage systems are a crucial component in balancing energy supply and demand on islands. The system inputs load demand time-series data and power generation unit configuration data into a multi-objective optimization configuration model for the energy storage system. With the goals of maximizing power supply reliability and minimizing operating costs, it optimizes the rated capacity, rated power, and state-of-charge (SOC) operating range of the energy storage system. Based on this, the system further develops multi-timescale charging and discharging scheduling strategies—planning charging and discharging for the next 24 hours at the day-ahead level, rolling corrections based on real-time forecast deviations at the intraday level, and achieving second-level response through power balance control at the real-time level—thus ensuring the energy storage system operates efficiently and reliably across all time scales.

[0142] Step 5: Co-generation of electricity and water:

[0143] The island's freshwater and energy supplies are highly coupled, and this step achieves joint optimization of both. The system incorporates the electricity demand of the seawater desalination system into the comprehensive load system and utilizes the waste heat from the power generation system (especially diesel generator sets and internal combustion engines) as a heat source for the seawater desalination system in a cascade manner. Through the combined power-water generation coordinated configuration function, the system simultaneously optimizes the configuration scheme of electricity and freshwater supply under a unified optimization framework, achieving efficient and coordinated utilization of energy and water resources.

[0144] Step Six: Multi-timescale joint simulation verification and scheme iterative optimization:

[0145] After the configuration scheme is finalized, it enters a rigorous simulation verification and optimization phase. The system integrates the configuration schemes of the above modules into an initial comprehensive configuration scheme, and conducts hourly simulation verification for 8760 hours throughout the year based on a multi-timescale joint simulation platform. The simulation covers three time scales: second-level power electronic transients, minute-level power balance, and hourly energy dispatch, comprehensively evaluating the power supply reliability, water supply reliability, and economic indicators of the scheme under various typical scenarios. If the simulation results do not meet the preset thresholds, the system iteratively optimizes the configuration parameters through equations until all constraints are met, generating the optimal configuration scheme.

[0146] Step 7: Deployment and grid connection of the energy supply system:

[0147] Once the optimal configuration scheme is determined, the actual deployment phase begins. Based on the scheme, the system deploys photovoltaic arrays, wind turbine generators, wave energy conversion devices, energy storage systems, seawater desalination systems, and intelligent energy management systems on the island. Through intelligent monitoring terminals deployed at each power generation unit, energy storage unit, and load node, the system collects multi-source data in real time, including power generation, energy storage status of charge, load power, environmental parameters, and equipment health status. This data is then aggregated to a central monitoring platform for unified processing, generating system operation status monitoring data to provide data support for real-time scheduling and optimization.

[0148] Step 8: Real-time scheduling optimization and adaptive adjustment:

[0149] The system possesses real-time sensing and adaptive optimization capabilities. Based on system operation status monitoring data, the system performs real-time assessments of renewable energy generation forecast deviations, load demand forecast deviations, and equipment operating status. When a forecast deviation exceeds a preset threshold or an abnormal operating condition occurs in the equipment, the system immediately triggers a real-time scheduling optimization process. Through a rolling time-domain optimization scheduling model, it solves for the optimal scheduling command within a finite time domain and sends the command to the actuators of each power generation unit, energy storage system, and adjustable load, thus dynamically adjusting the system's operating status. This forms a complete closed loop from resource exploration, optimized configuration, simulation verification, deployment and operation to real-time scheduling, continuously improving the operational efficiency and resource utilization efficiency of the island's energy supply system.

[0150] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0151] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for configuring energy supply on an island, characterized in that, The method includes the following steps: S1. Conduct multi-energy resource exploration and energy endowment assessment of the islands to generate island energy resource endowment characteristic data; S2. Based on the island's energy resource endowment characteristic data, perform preliminary configuration processing of multi-energy complementary power generation units to generate multi-energy complementary power generation unit configuration scheme data. S3. Based on the configuration scheme data of the multi-energy complementary power generation unit, perform island load demand prediction and dynamic characteristic analysis to generate island load demand time series characteristic data. S4. Based on the time-series characteristic data of the island's load demand, perform energy storage system capacity optimization configuration and charging / discharging strategy planning to generate energy storage system configuration scheme data and charging / discharging scheduling strategy data. S5. Based on the energy storage system configuration scheme data and the charging and discharging scheduling strategy data, perform co-generation of electricity and water to generate co-generation system configuration scheme data. S6. Based on the configuration scheme data of the multi-energy complementary power generation unit, the configuration scheme data of the energy storage system, and the configuration scheme data of the combined power and water system, perform multi-time-scale joint simulation verification and scheme iterative optimization to generate the optimal configuration scheme data for island energy supply. S7. Based on the optimal configuration scheme data for island energy supply, deploy and connect the energy supply system to the grid, and generate system operation status monitoring data; S8. Based on the system operation status monitoring data, perform real-time scheduling optimization and adaptive adjustment processing to generate dynamic scheduling optimization instruction data and updated system operation parameter data.

2. The method for configuring energy supply on an island according to claim 1, characterized in that, The process of generating island energy resource endowment characteristic data in S1 includes the following steps: S11. By deploying meteorological monitoring stations and marine monitoring buoys at various points on the island, collect data on annual solar radiation intensity, wind speed sequence, wave height and period, tidal current speed and direction, and generate raw multi-energy resource monitoring data. S12. The original multi-energy resource monitoring data is reported to the data center, and the resource assessment engine performs resource potential assessment and uncertainty quantification on various energy resources according to the preset energy resource assessment model, generating data on the annual average utilization hours, guaranteed output rate and fluctuation coefficient of various energy resources. S13. Based on the annual average utilization hours, guaranteed output rate and fluctuation coefficient data of the various types of energy resources, combined with the island's geospatial information, available land area and sea area usage conditions, construct a multi-dimensional energy endowment vector with resource category as the dimension, and aggregate to generate the island's energy resource endowment characteristic data.

3. The method for configuring energy supply on an island according to claim 2, characterized in that, The process of generating multi-energy complementary power generation unit configuration scheme data in S2 includes the following steps: S21. Obtain the energy resource endowment characteristics data of the island; S22. Based on the multi-energy complementary optimization configuration model, with the goal of optimizing the system's full life-cycle economy and constrained by power supply reliability, the installed capacity of photovoltaic power generation units, wind power generation units, wave power generation units, and diesel power generation units is jointly optimized. The capacity configuration of each power generation unit is achieved through the following optimization objective function: in, This represents the total cost over the entire system lifecycle. This represents the total number of power generation unit types. For the first The unit capacity investment cost of the power generation unit, For the first Configuration capacity of the power generation unit, For the first The unit power generation operation and maintenance cost of this type of power generation unit. For the first Annual power generation of the type of power generation unit For the unit cost of diesel fuel, For the first Diesel consumption during a given time period. For the first Class of power generation units in the first Efforts during a specific time period and The energy storage system in the first Discharge power and charging power during the time period For the first Load demand during different time periods This is the power supply reliability margin factor. For time period index, This represents the total number of time periods; S23. Based on the optimized configuration results, generate recommended installed capacity and corresponding output curve data for various types of power generation units, which will be used as the configuration scheme data for the multi-energy complementary power generation units.

4. The method for configuring energy supply on an island according to claim 3, characterized in that, The process of generating island load demand time-series characteristic data in S3 includes the following steps: S31. Obtain historical electricity load data, seasonal tourist flow data, residential energy consumption data, and seawater desalination water demand data for the island; S32. Based on the time series decomposition method, load demand is decomposed into trend components, seasonal components, periodic components, and random residual components, and the hourly load demand forecast data for the whole year is generated through the following load forecasting model: in, For the first Forecasted load demand for the specified period As a trend component, The harmonic order of the seasonal component. and The first The amplitude and phase of the first harmonic. For the corresponding seasonal cycle, Let the order be the autoregressive order. These are the autoregressive coefficients. For the first Actual load value for the time period For random residuals; S33. Perform peak-valley characteristic analysis, volatility analysis, and extreme scenario extraction on the hourly load demand forecast data for the whole year to generate the island load demand time series characteristic data containing typical daily load curves, seasonal load characteristics, and peak load scenarios.

5. The method for configuring energy supply on an island according to claim 4, characterized in that, The steps involved in generating energy storage system configuration scheme data and charge / discharge scheduling strategy data in step S4 are as follows: S41. Obtain the island load demand time-series characteristic data and the multi-energy complementary power generation unit configuration scheme data; S42. Based on the multi-objective optimization configuration model of the energy storage system, with the objectives of maximizing system power supply reliability and minimizing system operating costs, the rated capacity, rated power, and state-of-charge operating range of the energy storage system are optimized. The energy storage capacity configuration is achieved through the following multi-objective optimization function: in, For the total lifecycle cost of energy storage systems, Cost per unit power of energy storage This is the rated power of the energy storage. Cost per unit capacity of energy storage For the rated capacity of energy storage, The lifetime degradation cost per unit throughput of energy storage. The system power supply failure rate, For the first The probability of load loss during a given period; S43. Based on the state of charge constraints and charge / discharge efficiency characteristics of the energy storage system, formulate a multi-timescale charge / discharge scheduling strategy. The charge / discharge scheduling strategy includes three levels: day-ahead planning scheduling, intraday rolling correction, and real-time power balance. Generate the energy storage system configuration scheme data and charge / discharge scheduling strategy data.

6. The method for configuring energy supply on an island according to claim 5, characterized in that, The steps involved in generating the combined power and water production system configuration data in S5 are as follows: S51. Obtain the configuration scheme data of the multi-energy complementary power generation unit and the configuration scheme data of the energy storage system; S52. Based on the energy-freshwater coupling optimization model, the electricity demand of the seawater desalination system is incorporated into the comprehensive load system, and the waste heat from the power generation system is used as a heat source for seawater desalination in a cascade manner. Joint optimization is achieved through the following cogeneration coordination configuration function: in, The target value for the comprehensive optimization of the combined power and water generation system, The total lifecycle cost of a combined power and water system. The total cost of the baseline solution, The system power supply failure rate, The load failure rate is the baseline scheme. To address the freshwater supply shortage. For total freshwater demand, , , These are the weighting coefficients for cost, power supply reliability, and water supply reliability, respectively. For the first Power consumption of the seawater desalination system during a given period For the first Surplus power of the power generation system during certain periods For the first Reserved power available for use by the time-of-use energy storage system. For the first The amount of heat required by the seawater desalination system during a given period For waste heat recovery efficiency, For the first The time-of-use power generation system can recover waste heat; S53. Based on the optimization solution results of the combined power and water production configuration function, generate the installed capacity, daily water production, and coupling operation scheme of the seawater desalination system with the power generation system, as the configuration scheme data of the combined power and water production system.

7. The method for configuring energy supply on an island according to claim 6, characterized in that, The process of generating the optimal energy supply configuration scheme data for the island in S6 includes the following steps: S61. Integrate the configuration scheme data of the multi-energy complementary power generation unit, the configuration scheme data of the energy storage system, and the configuration scheme data of the combined power and water system into an initial comprehensive configuration scheme. S62. Based on a multi-timescale joint simulation platform, the initial integrated configuration scheme is simulated and verified hourly for 8760 hours throughout the year. The simulation dimensions include second-level power electronic transient simulation, minute-level power balance simulation and hour-level energy dispatch simulation. The scheme's power supply reliability, water supply reliability and economic indicators are evaluated under various typical scenarios. S63. If the simulation verification results do not meet the preset reliability and economic thresholds, the configuration parameters shall be corrected by iteratively optimizing the following scheme: in, Indicates the first The set of configuration parameters for round iteration. For learning rate, To comprehensively optimize the objectives Regarding configuration parameters gradient, The momentum coefficient; Iterate until the convergence condition is met to generate the optimal energy supply configuration scheme data for the island.

8. The method for configuring energy supply on an island according to claim 7, characterized in that, The process of generating system operation status monitoring data in S7 includes the following steps: S71. Based on the optimal configuration scheme data for island energy supply, deploy photovoltaic arrays, wind turbine generators, wave energy conversion devices, energy storage systems, seawater desalination systems, and intelligent energy management systems on the island site. S72. Through intelligent monitoring terminals deployed in each power generation unit, energy storage unit and load node, real-time data on power generation, energy storage state of charge, load power, environmental parameters and equipment health status are collected. S73. The collected multi-source data is aggregated to the central monitoring platform, and data cleaning, alignment and fusion processing are performed to generate the system operation status monitoring data.

9. The method for configuring energy supply on an island according to claim 8, characterized in that, The process of generating dynamic scheduling optimization instruction data and updated system operating parameter data in S8 includes the following steps: S81. Based on the system operation status monitoring data, perform real-time assessment of renewable energy power generation forecast deviation, load demand forecast deviation and equipment operation status. S82. When a prediction deviation is detected to exceed a preset threshold or an abnormal operating condition occurs in the equipment, a real-time scheduling optimization process is triggered, generating dynamic scheduling instructions through the following rolling time-domain optimization scheduling model: in, To optimize the time domain length, For the first System operating costs during a given period For the first System power imbalance during different time periods and These are operating cost weights and power balance weights, respectively. For the first The state of charge of the time-of-use energy storage system and These are the lower and upper limits of the state of charge, respectively. For the first Class of power generation units in the first Efforts during a specific time period Its rated power; S83. The dynamic scheduling command is sent to each power generation unit, energy storage system and the actuator of the adjustable load to complete the dynamic adjustment of the system operation status and generate the updated system operation parameter data.

10. An island energy supply configuration system for implementing the island energy supply configuration method according to any one of claims 1-9, characterized in that, The system includes an island multi-energy resource exploration and assessment module, a multi-energy complementary power generation configuration module, a load demand analysis and forecasting module, an energy storage system optimization configuration module, a combined power and water generation collaborative configuration module, a joint simulation and scheme optimization module, and a real-time scheduling and adaptive control module. The island multi-energy resource exploration and assessment module collects solar radiation, wind speed, wave and tide data of the island through meteorological and marine monitoring probe units, and performs potential assessment and quantification of various energy resources through resource assessment and standardization units to generate unified energy resource endowment characteristic data. The multi-energy complementary power generation configuration module receives the energy resource endowment characteristic data, performs joint optimization configuration of the capacity of photovoltaic, wind power, wave energy and diesel power generation units through the multi-energy complementary optimization unit, and outputs multi-energy complementary power generation unit configuration scheme data through the power generation scheme generation unit. The load demand analysis and forecasting module receives historical load data and external influencing factor data of the island, generates load demand time series characteristic data through the time series decomposition and forecasting unit, and outputs typical daily load curves and extreme scenario data through the load characteristic analysis unit. The energy storage system optimization configuration module receives the load demand time-series characteristic data and the power generation unit configuration scheme data, determines the rated power and rated capacity of the energy storage system through the energy storage capacity optimization unit, and generates multi-time-scale charging and discharging scheduling strategy data through the charging and discharging strategy planning unit. The combined power and water production configuration module receives the power generation configuration scheme and the energy storage configuration scheme, and performs joint optimization of the seawater desalination system capacity and the power generation waste heat utilization scheme through the electric-water coupling optimization unit, and outputs the combined power and water production system configuration scheme data. The joint simulation and scheme optimization module receives the configuration scheme data from the above modules, performs hourly simulation evaluation throughout the year through the multi-timescale simulation verification unit, and corrects the parameters of schemes that do not meet the constraints through the scheme iteration optimization unit, and outputs the optimal configuration scheme data for island energy supply. The real-time scheduling and adaptive control module receives system operation status monitoring data, detects the prediction deviation between power generation and load in real time through the prediction deviation evaluation unit, generates dynamic scheduling optimization instructions through the rolling time domain optimization scheduling unit, and completes the dynamic adjustment of system operation status through the execution control unit.

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